An introduction to machine learning interpretability an applied perspective on fairness, accountability, transparency, and explainable AI
Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate, but can also make their predictions difficult to understand. When accuracy outpaces interpretability, huma...
| Otros Autores: | , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media
[2019]
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| Edición: | Second edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630888306719 |
